Lifetime Engineering (or Life Cycle Engineering) is a technical approach for meeting the current objective of sustainable development. The approach is aimed to turn today’s reactive and short-term design, management and maintenance planning towards an optimised and long-term technical approach. The life cycle based management and maintenance planning approach includes condition assessment, predictive modelling of performance changes, maintenance analysis and maintenance, repair and refurbishment (MR&R) planning and decisions. The change towards a predictive approach requires generic systems, applicable to different maintenance manager organisations with different MR&R strategies, managing different types of construction works. The newly developed Life Cycle Management System (LMS) is a predictive and generic life cycle based management system aimed to support all types of decision making and planning of optimal MR&R activities of any construction works. The system takes into account a number of aspects in sustainable and conscious development such as human requirements, life cycle economy, life cycle ecology and cultural requirements. The LMS is a system by which the complete system or parts thereof, works in co-operation or as a complement to existing business support systems. This imply development and adaptation of the system in order to meet the user needs and requirements, a process which is to be geared and governed by the user. The scope of this paper is focused on development and adaptation of the predictive characteristic of LMS towards a presumptive user. The objective is to develop and adapt a Service Life Performance Analysis (SLPA) module applicable for condition based Facility Management System in general and for condition based Bridge Management System in particular. Emphasis is placed on development and adaptation of a conditional probability based SLPA model in which degradation models and Markov chains play a decisive role. The paper deals also with development and adaptation of environmental exposure data recording and processing, with special emphasis on quantitative environmental classification in order to provide a simplified method of SLPA.